In the reproduction of copies of an original document from video image data created, for example, by electronic input scanning from an original document, it is often desirable to provide functions dependent upon determining the exterior edges of the document. Such features include, for example, automatic magnification, automatic two-up copying, deletion of background image data which falls outside the detected exterior edges of the document to avoid storing a document requiring more space than necessary, automatic location of the document in a scanning system, electronic registration and deskewing of the electronic image, etc. In other words, to provide these features, the exterior edges of the document must somehow be detected by the scanning system.
In addition to the features identified above, the identification of the exterior edges of the document is necessary when scanning a document fed with a constant velocity transport (CVT) device, especially in a center-registered document feeding system. Typically, an edge detection operation is used to determine the arrival, as well as the side edges of individual input documents so as to set the start/stop coordinates and thereby identify the image area for capture and processing. That is, the scanner uses the edge detection operation to determine the presence, exact location, and size of a document being imaged in a CVT device. Such registration operation becomes extremely important issue in the case of dual head scanners to ensure that the front and backside of a scanned page is perfectly aligned.
As should be appreciated, to provide an edge detection operation the exterior edges of the document must somehow be detected by the scanning system. Conventionally, to achieve the detection of the exterior edges of the original document, digital scanners use a backing (e.g., a platen cover or, in a CVT, a baffle or ski) that is readily distinguishable from the original document. That is, edge detection typically relies on the ability of the digital scanner and/or the image processing system to sense a difference, such as the difference in reflectance between the input document's background and the surrounding backing, e.g., the platen cover, backing plate, baffle, ski, etc. Traditionally, the difference between the grayscale values of the scanner backing and the document was used for edge detection. To enable such detection, the document is preferably passed between the scanner and a black (or other dark color) backing. However, backings with a yellow color, a whiter than white color, a backing which fluoresces, and various other alternatives have also been employed.
Although various alternatives have been utilized, it is desirable to utilize a dark backing when scanning an original document so as to eliminate show through when scanning a double-sided or watermarked document (especially for thin or partially translucent originals). Utilizing a light absorbing backing (e.g., black or dark color) eliminates show through when scanning the document and enables the scanning system or other downstream image processing system to automatically locate the exterior edges of the original document. However, an undesirable consequence of using a light absorbing backing is that any defect in the original document; such as holes, cuts, rips, dog-ears, etc. or other characteristic properties of the original; such as pre-punched holes, etc.; appear as dark objects (also referred to as a scanning artifact) when they are displayed electronically or rendered and printed on a recording medium, whether they are printed immediately, faxed or subsequently or remotely printed.
Various image processing systems are available for recognizing, and eliminating by image processing, scanning artifacts corresponding to defects in the originals. One such solution proposes the use of two sets of color sensitive sensors (photosites), each set being sensitive to a different color of light and a backing having a predetermined color. The predetermined color of the backing is selected such that it appears nearly black to one set of sensors and appears nearly white to a different set of sensors. For example, the system might include a backing that is a saturated yellow with a set of sensors that is sensitive to blue being used for edge detection and a set of sensors that is sensitive to green being used for image capture. Such a solution can be used with color scanners wherein a single channel, such as blue may used for edge detection and registration with all three sensors (red, green, blue) being used for image capture.
While systems and methods based on the solutions above provide good detection and artifact removal, they are not appropriate for every application. For example, when scanning in a color space such as YCbCr or Lab, dynamic registration based on grayscale contribution may not be feasible. Additionally, in some applications the document and the color of the ski may be such that there may not be sufficient luminance variation between the document and the color of the ski in any channel to enable accurate document registration.
In accordance with the teachings herein, there is disclosed a method for dynamic registration using chrominance information. Briefly, an embodiment of a detection algorithm will look for an appreciable difference in chrominance levels to perform edge detection. To calibrate, a small scan is performed to determine the color of the backing/ski in the document feeder. Based on the detected color and video statistics (e.g., chrominance mean and deviation) of the backing/ski, appropriate channel and suitable set of registration parameters are calculated for automatic registration of documents. The calculated registration parameters are then used to automatically register documents supported by the backing/ski.
In accordance with another aspect of the teachings herein, there is provided a method of automatically detecting registration parameters for a selected backing surface. The method includes obtaining image data comprising a representative sample of the backing surface, the image data including chrominance values for selected pixel locations along a scanline; determining an average chrominance value for at least one channel; determining a chrominance deviation; and determining registration parameters based on the average chrominance value and the chrominance deviation.
In accordance with another aspect of the teachings herein, there is disclosed a method of edge detection using multiple channels. The method includes receiving scanned image data for a plurality of channels; performing an edge detection operation using image data from a first channel to identify a first detected edge; performing an edge detection operation using image data from a second channel to identify a second detected edge; and performing a resolution operation to identify an actual document edge from the first detected edge and the second detected edge.